--- title: Blurry keywords: fastai sidebar: home_sidebar summary: "**Blurry** detects faces in photos and blurs them to increase privacy." description: "**Blurry** detects faces in photos and blurs them to increase privacy." nb_path: "00_core.ipynb" ---
Helper function to show cv2 images in Jupyter notebook
Simple Gaussian blur
Testing blur:
test_img = cv2.imread('test_images/small.jpg')
assert test_img.shape == blur(test_img).shape, "Function should not change shape of array"
assert test_img.shape == blur(test_img, factor=0.5).shape, "Factors < 1 should work"
tiny = np.zeros((5,5,3), dtype = np.uint8)
assert tiny.shape == blur(tiny, factor=10).shape, "Blur function should work also when kernel size > image size"
def image_row(*images: list, from_cv2=True, figsize=(12,6), **kwargs) -> None :
n_of_images = len(images)
fig, axes = plt.subplots(1, n_of_images, figsize=figsize, **kwargs)
#fig.tight_layout()
for ax, img in zip(axes, images):
if from_cv2:
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
ax.imshow(img)
ax.set_axis_off()
image_row(test_img, blur(test_img), blur(test_img, factor=0.5), figsize=(10,5))
Test pixelate:
assert test_img.shape == pixelate(test_img).shape, "Function should not change shape of array"
assert len(np.unique(test_img)) > len(np.unique(pixelate(test_img))), "Number of unique colors should have been reduced"
assert len(np.unique(pixelate(test_img, factor=0.5))) > len(np.unique(pixelate(test_img, factor=5))), "Large factor should reduce number of unique colors"
tiny = np.zeros((5,5,3), dtype = np.uint8)
assert tiny.shape == pixelate(tiny).shape, "Pixelate function should also work on tiny images"
image_row(test_img, pixelate(test_img), pixelate(test_img, factor=1.5), figsize=(10,5))
group_img = cv2.imread('test_images/group.jpg')
faces = find_faces(group_img)
assert len(faces) == 7, "there should be 7 faces in the group test image"
Does it work?
img = group_img.copy()
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
show_cv2(img)
img = load_img('test_images/group_closer.jpg')
show_cv2(anonymize(img, factor=1, mode='pixelate'))
img = load_img('test_images/group_closer.jpg')
show_cv2(anonymize(img, factor=1))
def test_bulk(directory, **kwargs):
path = Path(directory)
for fn in path.ls():
blurred = anonymize(load_img(fn), **kwargs)
show_cv2(blurred)
test_bulk('test_images', factor=1, mode='pixelate')